Must Skills for Data Engineering

A Data Engineer conceives, builds and maintains data infrastructure that holds your enterprises advanced analytics capacities together. Data Engineers are problem solvers focused on building and maintaining infrastructure and architecture for data generation

The required Skills Are:

1.Python

•Programming provides us a way to communicate with machines.

•Python: It is one of the easiest to learn a programming language and has the richest library. 

2.SQL

•You can’t get away from learning about databases when you are aspiring to become a data engineer. 

•SQL databases are relational databases that store data in multiple related tables SQL is a must-have skill for every data professional.

3.Big Data

•Big Data engineering is a specialization wherein professionals work with Big Data and it requires developing, maintaining, testing, and evaluating big data solutions.

4.Apache Hadoop

•Apache Hadoop is an open-source framework that lets you store and manage Big Data applications.

•Hadoop lets you perform distributed processing of large datasets by using simple programming implementations. 

5.Apache Hive

•Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. 

6.Kafka

•Kafka is an open-source processing software platform for handling real-time data feeds. 

• It means you can use it to build real-time streaming apps, which is something that businesses require.

7.Apache Spark

•Apache Spark is another must-have tool you must be familiar with if you want to become a data engineer. 

•Spark is an open-source distributed general-purpose framework for cluster computing. It offers an interface that lets you program clusters with fault tolerance and data parallelism.

8.ETL

•ETL stands for Extract, Transfer, Load, and denotes how you extract data from a source, transform it into a format, and store it into a data warehouse

•ETL uses batch processing to ensure users can analyze relevant data according to their specific business problems. 

9.Scala

• Python is a must-have for a data engineer as it helps you perform statistical analysis and modelling. On the other hand, Java helps you work with data architecture frameworks and Scala is simply an extension of the same.

•Scala: When it comes to data engineering, the spark is one of the most widely used tools and it is written as Scala. Scala is an extension of the Java language. 

10.Database Skills and tools

•This is a different type of distributed data storage that’s becoming increasingly popular. Simply explained, the name “NoSQL” means technology based on something different from SQL.